Probability of detection (POD) is being introduced as a standard measurement for quantifying the reliability and robustness of built-in structural health monitoring systems. It has become common practice to quantify the reliability of flaw detection in terms of the probability of detection (POD).
POD tries to assess a minimum flaw size that will be reliably detected by a non-destructive testing (NDT) technique. This is best done by plotting the accumulation of flaws detected against the flaw size of all the flaws “detected,” where “detected” may mean producing a signal response that exceeds some threshold. Ideally all flaws over some critical size will be detected and smaller flaws are not “detected”. The tool most commonly used for POD description is the POD curve. The POD curve is useful in providing a reference method of quantifying the performance capability of an NDT procedure.
However, traditional POD curves are typically generated for single points and are obtained through extensive testing, which is not practical for every new structure and transducer array configuration. Structural health monitoring, e.g., the detection and location of defect damage in a structure, using an array of transducers, where the transducers may serve both as actuators and sensors, may require a modified or different approach. Experimental measurement may be expensive and yield answers based on poor statistics which may be caused, for example, by noise in the detection system, or a lack of sufficient test data; therefore attention has recently turned to modeling. To overcome this difficulty it is desirable to have a method to predict the POD for the entire structure, or any sub-region thereof, using merely the transducer coordinates, the operating actuator-sensor paths and the logic of a given damage detection process.